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Practical recipes and code for applying computational methods—text mining, topic modeling, network analysis, and spatial/archival techniques—to humanities resea
Presents a practical toolkit for researchers in the humanities to apply computational methods: corpus preparation, TF-IDF and topic modeling (LDA), social network analysis for correspondence, GIS/spatial humanities workflows, TEI archival encoding, and ethical considerations. The skill includes code snippets (Python) demonstrating preprocessing, TF-IDF, LDA topic modeling, and network construction.
Use when conducting digital humanities projects that require text analysis, topic discovery, mapping historical data, building correspondence networks, or preparing TEI-compliant digital editions. Useful for scholars transitioning from traditional qualitative work to reproducible quantitative methods.
Good fit for research-assistant agents and Python-capable toolchains (e.g., Codex/GPT code models, research automation agents).
A reference-style skill providing inline Python code snippets for digital humanities research methods (TF-IDF, LDA topic modeling, NetworkX correspondence analysis, TEI XML encoding). No executable scripts or workflow — it functions as a cookbook rather than an actionable agent skill. Code snippets are well-commented with docstrings but are illustrative, not runnable as a pipeline. No security concerns whatsoever; purely static reference content with no network calls, credentials, or destructive operations.
This is a reference document masquerading as a skill. It has no triggers, no workflow steps, no output contracts, and no automation. The code examples are pedagogically sound but not operationalized. Would benefit from being restructured into an actual skill with scripts/ and a step-by-step workflow, or recategorized as a reference rather than a skill.
Obsidian CLI
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KFL2 (Kubeshark Filter Language)
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Open GIS Toolkit
Production-grade geospatial workflows using an open-first stack for spatial analysis and web mapping.
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Advanced spatial analysis for vector data including coordinate reprojection, spatial joins, and choropleth mapping using the GeoPandas library.
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Python package for creating, manipulating, and analyzing complex networks and graphs.
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Expert coding skill for the full MapTiler platform, including SDKs and Cloud APIs.